Total variation approximation for quasi-equilibrium distributions
A. D. Barbour, P. K. Pollett

TL;DR
This paper introduces a method to approximate quasi-stationary distributions in biological models using total variation, ensuring existence, uniqueness, and computational simplicity under certain conditions.
Contribution
It provides biologically plausible conditions for the existence and uniqueness of quasi-stationary distributions and offers a practical approximation method.
Findings
Conditions for uniqueness of quasi-stationary distributions
Total variation approximation method developed
Simplifies computation of long-term population behavior
Abstract
Quasi-stationary distributions, as discussed by Darroch & Seneta (1965), have been used in biology to describe the steady state behaviour of population models which, while eventually certain to become extinct, nevertheless maintain an apparent stochastic equilibrium for long periods. These distributions have some drawbacks: they need not exist, nor be unique, and their calculation can present problems. In this paper, we give biologically plausible conditions under which the quasi-stationary distribution is unique, and can be closely approximated by distributions that are simple to compute.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMarkov Chains and Monte Carlo Methods
